Traditional Key Performance Indicators (KPIs) are widespread in their use, but also have limitations. For example, in a “Smarter Cities” usage, it is frequently insufficient to track the performance of indicators at an aggregated level, irrespective of space and time. Technologies endeavor to create smarter cities of the future that will drive sustainable economic growth. Leaders of smarter cities will have the tools to analyze data for better decisions, anticipate problems to resolve them proactively and coordinate resources to operate effectively. As demands grow and budgets tighten, solutions also have to be smarter, and address the city as a whole. By collecting and analyzing the extensive data generated every second of every day, technology will be used to coordinate and share data in a single view creating the big picture for the decision makers and responders who support the smarter city.
By definition, Smarter City-based use cases are concerned with geospatial and temporal distribution of data sets, and by consequence, the tracking of these data sets as KPIs frequently requires the consideration of space and time. For example, the tracking of crowd density at key points across a city can be used for various reasons, perhaps for crowd control for a concert or public event. Simply tracking numbers of citizens, or crowd density is insufficient. Typically the operator wishes to see visually, over multiple locations the current indicators. However, traditional KPIs are insufficient with regards to visually depicting future values of indicators at various locations and times.